# app.py import gradio as gr from bs4 import BeautifulSoup import requests from sentence_transformers import SentenceTransformer import faiss import numpy as np import asyncio import aiohttp import re import base64 import logging import os # Import OpenAI library import openai # Set up logging logging.basicConfig(filename='app.log', level=logging.INFO, format='%(asctime)s %(levelname)s %(name)s %(message)s') logger = logging.getLogger(__name__) # Initialize models and variables logger.info("Initializing models and variables") embedding_model = SentenceTransformer('all-MiniLM-L6-v2') faiss_index = None bookmarks = [] fetch_cache = {} # Define the categories CATEGORIES = [ "Social Media", "News and Media", "Education and Learning", "Entertainment", "Shopping and E-commerce", "Finance and Banking", "Technology", "Health and Fitness", "Travel and Tourism", "Food and Recipes", "Sports", "Arts and Culture", "Government and Politics", "Business and Economy", "Science and Research", "Personal Blogs and Journals", "Job Search and Careers", "Music and Audio", "Videos and Movies", "Reference and Knowledge Bases", "Dead Link", "Uncategorized", ] # Set up Groq Cloud API key and base URL GROQ_API_KEY = os.getenv('GROQ_API_KEY') if not GROQ_API_KEY: logger.error("GROQ_API_KEY environment variable not set.") raise ValueError("Please set the GROQ_API_KEY environment variable.") # Set OpenAI API key and base URL to use Groq Cloud API openai.api_key = GROQ_API_KEY openai.api_base = "https://api.groq.com/openai/v1" # Function to parse bookmarks from HTML def parse_bookmarks(file_content): logger.info("Parsing bookmarks") try: soup = BeautifulSoup(file_content, 'html.parser') extracted_bookmarks = [] for link in soup.find_all('a'): url = link.get('href') title = link.text.strip() if url and title: extracted_bookmarks.append({'url': url, 'title': title}) logger.info(f"Extracted {len(extracted_bookmarks)} bookmarks") return extracted_bookmarks except Exception as e: logger.error("Error parsing bookmarks: %s", e) raise # Asynchronous function to fetch URL info async def fetch_url_info(session, bookmark): url = bookmark['url'] if url in fetch_cache: bookmark.update(fetch_cache[url]) return bookmark try: logger.info(f"Fetching URL info for: {url}") async with session.get(url, timeout=5) as response: bookmark['etag'] = response.headers.get('ETag', 'N/A') bookmark['status_code'] = response.status if response.status >= 400: bookmark['dead_link'] = True bookmark['description'] = '' logger.warning(f"Dead link detected: {url} with status {response.status}") else: bookmark['dead_link'] = False content = await response.text() soup = BeautifulSoup(content, 'html.parser') # Extract meta description or Open Graph description meta_description = soup.find('meta', attrs={'name': 'description'}) og_description = soup.find('meta', attrs={'property': 'og:description'}) if og_description and og_description.get('content'): description = og_description.get('content') elif meta_description and meta_description.get('content'): description = meta_description.get('content') else: description = '' bookmark['description'] = description logger.info(f"Fetched description for {url}") except Exception as e: bookmark['dead_link'] = True bookmark['etag'] = 'N/A' bookmark['status_code'] = 'N/A' bookmark['description'] = '' logger.error(f"Error fetching URL info for {url}: {e}") finally: fetch_cache[url] = { 'etag': bookmark.get('etag'), 'status_code': bookmark.get('status_code'), 'dead_link': bookmark.get('dead_link'), 'description': bookmark.get('description'), } return bookmark # Asynchronous processing of bookmarks async def process_bookmarks_async(bookmarks): logger.info("Processing bookmarks asynchronously") try: async with aiohttp.ClientSession() as session: tasks = [] for bookmark in bookmarks: task = asyncio.ensure_future(fetch_url_info(session, bookmark)) tasks.append(task) await asyncio.gather(*tasks) logger.info("Completed processing bookmarks asynchronously") except Exception as e: logger.error(f"Error in asynchronous processing of bookmarks: {e}") raise # Generate summary for a bookmark def generate_summary(bookmark): description = bookmark.get('description', '') if description: bookmark['summary'] = description else: title = bookmark.get('title', '') if title: bookmark['summary'] = title else: bookmark['summary'] = 'No summary available.' logger.info(f"Generated summary for bookmark: {bookmark.get('url')}") return bookmark # Assign category to a bookmark def assign_category(bookmark): if bookmark.get('dead_link'): bookmark['category'] = 'Dead Link' logger.info(f"Assigned category 'Dead Link' to bookmark: {bookmark.get('url')}") return bookmark summary = bookmark.get('summary', '').lower() assigned_category = 'Uncategorized' # Keywords associated with each category category_keywords = { "Social Media": ["social media", "networking", "friends", "connect", "posts", "profile"], "News and Media": ["news", "journalism", "media", "headlines", "breaking news"], "Education and Learning": ["education", "learning", "courses", "tutorial", "university", "academy", "study"], "Entertainment": ["entertainment", "movies", "tv shows", "games", "comics", "fun"], "Shopping and E-commerce": ["shopping", "e-commerce", "buy", "sell", "marketplace", "deals", "store"], "Finance and Banking": ["finance", "banking", "investment", "money", "economy", "stock", "trading"], "Technology": ["technology", "tech", "gadgets", "software", "computers", "innovation"], "Health and Fitness": ["health", "fitness", "medical", "wellness", "exercise", "diet"], "Travel and Tourism": ["travel", "tourism", "destinations", "hotels", "flights", "vacation"], "Food and Recipes": ["food", "recipes", "cooking", "cuisine", "restaurant", "dining"], "Sports": ["sports", "scores", "teams", "athletics", "matches", "leagues"], "Arts and Culture": ["arts", "culture", "museum", "gallery", "exhibition", "artistic"], "Government and Politics": ["government", "politics", "policy", "election", "public service"], "Business and Economy": ["business", "corporate", "industry", "economy", "markets"], "Science and Research": ["science", "research", "experiment", "laboratory", "study", "scientific"], "Personal Blogs and Journals": ["blog", "journal", "personal", "diary", "thoughts", "opinions"], "Job Search and Careers": ["jobs", "careers", "recruitment", "resume", "employment", "hiring"], "Music and Audio": ["music", "audio", "songs", "albums", "artists", "bands"], "Videos and Movies": ["video", "movies", "film", "clips", "trailers", "cinema"], "Reference and Knowledge Bases": ["reference", "encyclopedia", "dictionary", "wiki", "knowledge", "information"], } for category, keywords in category_keywords.items(): for keyword in keywords: if re.search(r'\b' + re.escape(keyword) + r'\b', summary): assigned_category = category logger.info(f"Assigned category '{assigned_category}' to bookmark: {bookmark.get('url')}") break if assigned_category != 'Uncategorized': break bookmark['category'] = assigned_category if assigned_category == 'Uncategorized': logger.info(f"No matching category found for bookmark: {bookmark.get('url')}") return bookmark # Vectorize summaries and build FAISS index def vectorize_and_index(bookmarks): logger.info("Vectorizing summaries and building FAISS index") try: summaries = [bookmark['summary'] for bookmark in bookmarks] embeddings = embedding_model.encode(summaries) dimension = embeddings.shape[1] faiss_idx = faiss.IndexFlatL2(dimension) faiss_idx.add(np.array(embeddings)) logger.info("FAISS index built successfully") return faiss_idx, embeddings except Exception as e: logger.error(f"Error in vectorizing and indexing: {e}") raise # Generate HTML display for bookmarks def display_bookmarks(): logger.info("Generating HTML display for bookmarks") cards = '' for i, bookmark in enumerate(bookmarks): index = i + 1 # Start index at 1 status = "Dead Link" if bookmark.get('dead_link') else "Active" title = bookmark['title'] url = bookmark['url'] etag = bookmark.get('etag', 'N/A') summary = bookmark.get('summary', '') category = bookmark.get('category', 'Uncategorized') # Apply inline styles for dead links if bookmark.get('dead_link'): card_style = "border: 2px solid #D32F2F;" text_style = "color: #D32F2F;" else: card_style = "" text_style = "" card_html = f'''

{index}. {title}

Category: {category}

URL: {url}

Status: {status}

ETag: {etag}

Summary: {summary}

''' cards += card_html logger.info("HTML display generated") return cards # Process the uploaded file def process_uploaded_file(file): global bookmarks, faiss_index logger.info("Processing uploaded file") if file is None: logger.warning("No file uploaded") return "Please upload a bookmarks HTML file.", '' try: file_content = file.decode('utf-8') except UnicodeDecodeError as e: logger.error(f"Error decoding the file: {e}") return "Error decoding the file. Please ensure it's a valid HTML file.", '' try: bookmarks = parse_bookmarks(file_content) except Exception as e: logger.error(f"Error parsing bookmarks: {e}") return "Error parsing the bookmarks HTML file.", '' if not bookmarks: logger.warning("No bookmarks found in the uploaded file") return "No bookmarks found in the uploaded file.", '' # Asynchronously fetch bookmark info try: asyncio.run(process_bookmarks_async(bookmarks)) except Exception as e: logger.error(f"Error processing bookmarks asynchronously: {e}") return "Error processing bookmarks.", '' # Generate summaries and assign categories for bookmark in bookmarks: generate_summary(bookmark) assign_category(bookmark) try: faiss_index, embeddings = vectorize_and_index(bookmarks) except Exception as e: logger.error(f"Error building FAISS index: {e}") return "Error building search index.", '' message = f"Successfully processed {len(bookmarks)} bookmarks." logger.info(message) bookmark_html = display_bookmarks() return message, bookmark_html # Chatbot response using Groq Cloud API def chatbot_response(user_query): if not bookmarks: logger.warning("No bookmarks available for chatbot") return "No bookmarks available. Please upload and process your bookmarks first." logger.info(f"Chatbot received query: {user_query}") # Prepare the prompt for the LLM try: # Limit the number of bookmarks to prevent exceeding token limits max_bookmarks = 50 # Adjust as needed bookmark_data = "" for idx, bookmark in enumerate(bookmarks[:max_bookmarks]): bookmark_data += f"{idx+1}. Title: {bookmark['title']}\nURL: {bookmark['url']}\nSummary: {bookmark['summary']}\n\n" # Construct the prompt prompt = f""" You are an assistant that helps users find relevant bookmarks from their collection based on their queries. User Query: {user_query} Bookmarks: {bookmark_data} Please identify the most relevant bookmarks that match the user's query. Provide a concise list including the index, title, URL, and a brief summary. """ # Call the Groq Cloud API via the OpenAI client response = openai.ChatCompletion.create( model='llama3-8b-8192', # Specify the Groq Cloud model messages=[ {"role": "system", "content": "You help users find relevant bookmarks based on their queries."}, {"role": "user", "content": prompt} ], max_tokens=500, temperature=0.7, ) # Extract the response text answer = response['choices'][0]['message']['content'].strip() logger.info("Chatbot response generated using Groq Cloud API") return answer except Exception as e: logger.error(f"Error in chatbot response generation: {e}") return "Error processing your query." # Edit a bookmark def edit_bookmark(bookmark_idx, new_title, new_url, new_category): global faiss_index try: bookmark_idx = int(bookmark_idx) - 1 # Adjust index to match list (starting at 0) if bookmark_idx < 0 or bookmark_idx >= len(bookmarks): logger.warning(f"Invalid bookmark index for editing: {bookmark_idx + 1}") return "Invalid bookmark index.", display_bookmarks() logger.info(f"Editing bookmark at index {bookmark_idx + 1}") bookmarks[bookmark_idx]['title'] = new_title bookmarks[bookmark_idx]['url'] = new_url bookmarks[bookmark_idx]['category'] = new_category # Re-fetch bookmark info asyncio.run(process_bookmarks_async([bookmarks[bookmark_idx]])) generate_summary(bookmarks[bookmark_idx]) # Rebuild the FAISS index faiss_index, embeddings = vectorize_and_index(bookmarks) message = "Bookmark updated successfully." logger.info(message) updated_html = display_bookmarks() return message, updated_html except Exception as e: logger.error(f"Error editing bookmark: {e}") return f"Error: {str(e)}", display_bookmarks() # Delete selected bookmarks def delete_bookmarks(indices_str): global faiss_index try: indices = [int(idx.strip()) - 1 for idx in indices_str.split(',') if idx.strip().isdigit()] indices = sorted(indices, reverse=True) logger.info(f"Deleting bookmarks at indices: {indices}") for idx in indices: if 0 <= idx < len(bookmarks): logger.info(f"Deleting bookmark at index {idx + 1}") bookmarks.pop(idx) # Rebuild the FAISS index if bookmarks: faiss_index, embeddings = vectorize_and_index(bookmarks) else: faiss_index = None message = "Selected bookmarks deleted successfully." logger.info(message) updated_html = display_bookmarks() return message, updated_html except Exception as e: logger.error(f"Error deleting bookmarks: {e}") return f"Error: {str(e)}", display_bookmarks() # Export bookmarks to HTML def export_bookmarks(): if not bookmarks: logger.warning("No bookmarks to export") return None try: logger.info("Exporting bookmarks to HTML") # Create an HTML content similar to the imported bookmarks file soup = BeautifulSoup("Bookmarks

Bookmarks

", 'html.parser') dl = soup.new_tag('DL') for bookmark in bookmarks: dt = soup.new_tag('DT') a = soup.new_tag('A', href=bookmark['url']) a.string = bookmark['title'] dt.append(a) dl.append(dt) soup.append(dl) html_content = str(soup) # Encode the HTML content to base64 for download b64 = base64.b64encode(html_content.encode()).decode() href = f'data:text/html;base64,{b64}' logger.info("Bookmarks exported successfully") return href except Exception as e: logger.error(f"Error exporting bookmarks: {e}") return None # Build the Gradio app def build_app(): try: logger.info("Building Gradio app") with gr.Blocks(css="app.css") as demo: gr.Markdown("

Bookmark Manager App

") with gr.Tab("Upload and Process Bookmarks"): upload = gr.File(label="Upload Bookmarks HTML File", type='binary') process_button = gr.Button("Process Bookmarks") output_text = gr.Textbox(label="Output") bookmark_display = gr.HTML(label="Bookmarks") def update_bookmark_display(file): return process_uploaded_file(file) process_button.click( update_bookmark_display, inputs=upload, outputs=[output_text, bookmark_display] ) with gr.Tab("Chat with Bookmarks"): user_input = gr.Textbox(label="Ask about your bookmarks") chat_output = gr.Textbox(label="Chatbot Response") chat_button = gr.Button("Send") chat_button.click( chatbot_response, inputs=user_input, outputs=chat_output ) with gr.Tab("Manage Bookmarks"): manage_output = gr.Textbox(label="Manage Output") bookmark_display_manage = gr.HTML(label="Bookmarks") refresh_button = gr.Button("Refresh Bookmark List") indices_input = gr.Textbox(label="Bookmark Indices to Delete (comma-separated)") delete_button = gr.Button("Delete Selected Bookmarks") export_button = gr.Button("Export Bookmarks") download_link = gr.HTML(label="Download Exported Bookmarks") with gr.Row(): index_input = gr.Number(label="Bookmark Index (Starting from 1)", precision=0) new_title_input = gr.Textbox(label="New Title") new_url_input = gr.Textbox(label="New URL") new_category_input = gr.Dropdown(label="New Category", choices=CATEGORIES) edit_button = gr.Button("Edit Bookmark") def update_manage_display(): return display_bookmarks() refresh_button.click( update_manage_display, inputs=None, outputs=bookmark_display_manage ) edit_button.click( edit_bookmark, inputs=[index_input, new_title_input, new_url_input, new_category_input], outputs=[manage_output, bookmark_display_manage] ) delete_button.click( delete_bookmarks, inputs=indices_input, outputs=[manage_output, bookmark_display_manage] ) def provide_download_link(): href = export_bookmarks() if href: return f'Download Exported Bookmarks' else: return "No bookmarks to export." export_button.click( provide_download_link, inputs=None, outputs=download_link ) # Initial load of the bookmarks display bookmark_display_manage.value = update_manage_display() logger.info("Launching Gradio app") demo.launch(debug=True) except Exception as e: logger.error(f"Error building the app: {e}") print(f"Error building the app: {e}") if __name__ == "__main__": build_app()